Federator.ai® for OpenShift/Kubernates with Datadog
Container adoption is growing, and Kubernetes is becoming the de facto standard of container management platforms. Whether container adoption occurs on-premises, in public clouds, or both, the operational overhead is enormous. IT administrators cannot foresee computing resource demands of applications, so they must reserve more computing resources for a workload than needed. Managing computing resources and optimizing costs on multiple clouds are daunting tasks. Datadog is a robust monitoring platform for cloud applications. It aggregates metrics and events across systems, applications and services, and provide full visibility and traceability to the DevOps team. Utilizing the rich and comprehensive metrics from Datadog, Federator.ai, ProphetStor’s Artificial Intelligence for IT Operations (AIOps) platform, provides intelligence to orchestrate container resources on top of VMs (virtual machines) or bare metal, allowing users to operate applications without the need to manage the underlying computing resources.
Federator.ai for OpenShift/Kubernetes with Datadog can be deployed in either native Kubernetes environment or latest OpenShift environment that are under Datadog monitoring. Utilizing metrics collected by Datadog Agent, Federator.ai uses resource usage pattern and predicts the required resources from cluster node level down to namespace and deployment level. End users can view the displays of application workload prediction and resource recommendation from the easy-to-use Federator.ai UI or from custom Datadog Dashboards for a single pane of glass management. Here are the key features delivered by the Federator.ai for Datadog:
Multi-layer workload prediction:
Using machine learning and math-based algorithms, Federator.ai predicts containerized application and cluster node resource usage as the basis for resource recommendations at application level as well as at cluster node level. Federator.ai supports prediction for both physical/virtual CPUs and memories.
Auto-scaling via resource recommendation:
Federator.ai utilizes the predicted resource usage to recommend the right number and size of pods for applications. Integrated with Datadog’s WPA, applications are automatically scaled to meet the predicted resource usage.
Application-aware recommendation execution:
Optimizing the resource usage and performance goals, Federator.ai uses application specific metrics for workload prediction and pod capacity estimation to auto-scale the right number of pods for best performance without overprovisioning.
Multi-cloud Cost Analysis:
With resource usage prediction, Federator.ai analyzes potential cost of a cluster on different public cloud providers. It also recommend appropriate cluster nodes and instance types based on resource usage.
Custom Datadog Dashboards:
Predefined custom Datadog Dashboards for workload prediction/recommendation visualization for cluster nodes and applications.
Custom Datadog Dashboards for visualizing workload prediction
Federator.ai for OpenShift/Kubernetes with Datadog provides optimal resource planning recommendation to automatic pod scaling to help Datadog customers make better decisions and improve operational efficiency. The major benefits of Federator.ai for OpenShift/Kubernetes with Datadog include:
- Up to 70% resource savings: Federator.ai mainly serves to reduce unnecessary spending and increase application service quality for both enterprises and cloud providers. ProphetStor data scientists and engineering teams work together to build the most advanced AIOps solution to reduce resource wastage at different infrastructure layers. With the help of patented prediction technologies, Federator.ai simultaneously reduces spending and delivers the necessary performance.
- Increased operational efficiency: Federator.ai frees users from continuously monitoring OpenShift/Kubernetes cluster utilization and cloud spending. Users also do not need to manually record usage data, calculate optimal configurations, and change configurations based on the calculations. These tasks are routinely accomplished when using Federator.ai. Additional integration with Datadog monitors enables early notification of possible resource shortage based on usage prediction.
- Reduced manual configuration time with digital intelligence:
Federator.ai allows users to turn on the optimization engine at any time. Federator.ai will auto scale pods with the right numbers at the right time.
- Single pane of glass management with Datadog:Federator.ai provides a seamless upgrade for Datadog customers. With custom Datadog Dashboards and tight integration with Datadog monitoring service, users can manage/monitor clusters and applications all from the same single pane of glass.